Role: AI Engineer Level II
Location: Washington, DC - Onsite
Position Summary As an AI Engineer (Level II), you'll design and implement enterprise-grade AI systems with a focus on Retrieval-Augmented Generation (RAG), agentic AI, and cloud-native ML pipelines. You'll work cross-functionally to operationalize secure, scalable solutions across Azure and AWS platforms, contributing to production-ready, multi-modal GenAI applications.
Key Responsibilities AI Architecture & Delivery
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Design and deploy RAG pipelines using Azure AI/Search and vector DBs (Redis, FAISS, HNSW).
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Develop conversational AI systems with prompt lifecycle management, telemetry, and guardrails.
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Integrate LLMs like Azure OpenAI, Llama, Claude, and OSS models across vision and speech domains.
Infrastructure & Orchestration
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Implement Model Context Protocol (MCP) servers with RBAC, schema versioning, validation, and audit trails.
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Deploy Azure AI Agent Service patterns: agent registry, policy enforcement, and telemetry logging.
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Use Azure Batch and AWS EMR for parallel inferencing and distributed feature processing.
Data Pipeline Engineering
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Build and manage ingestion pipelines: document normalization, metadata enrichment, PII redaction, SLA monitoring.
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Operate scalable vectorization pipelines with drift detection and quality gates.
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Use Azure Data Factory and Databricks; AWS EMR for large-scale Hadoop/Spark workloads.
Agentic AI Development
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Implement secure tool-calling and multi-agent orchestration using Semantic Kernel, AutoGen, Agent Framework, CrewAI, Agno, and LangChain.
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Apply governance, telemetry, and lifecycle management across agent runtimes with MCP controls.
Model Ops & Evaluation
Software Engineering Core -
Proficiency in CS fundamentals: algorithms, distributed systems, concurrency, networking.
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Experience with SDLC excellence: clean architecture, SOLID, testing pyramids (unit, integration, E2E).
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Secure AI app development: input validation, secret hygiene, RBAC, sandboxed functions.
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Performance engineering: latency tuning, token optimization, vector index profiling.
Cloud AI Tech Stack Azure: Azure OpenAI, AI/Search, AML, AKS, Azure Functions, Key Vault, ADF, Databricks, Azure Batch
AWS: SageMaker, Bedrock, Lambda, EMR, Comprehend, API Gateway, S3, EKS
Vector DBs: Azure AI Search, Redis, FAISS/HNSW
Frameworks: Semantic Kernel, AutoGen, Microsoft Agent Framework, CrewAI, Agno, LangChain
Inference: Docker/Ollama, vLLM, GPU provisioning, quantization (GGUF)
Qualifications Education: Bachelor's in CS, Engineering, or equivalent hands-on expertise
Experience: 5+ years in software engineering; 2+ years in GenAI/LLM applications (RAG, agents, safety, eval)
Certifications (Required) -
Microsoft Certified: Azure AI Fundamentals (AI-900)
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Microsoft Certified: Azure Data Fundamentals (DP-900)
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Responsible AI certifications
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AWS Machine Learning Specialty
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TensorFlow Developer
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Kubernetes CKA or CKAD
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SAFe Agile Software Engineering
Preferred:
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Azure AI Engineer Associate (AI-102)
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Azure Data Scientist Associate (DP-100)
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Azure Solutions Architect (AZ-305)
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Azure Developer Associate (AZ-204)
Required Skills/Abilities: - GenAI architecture mastery: RAG, vector DBs, embeddings, transformer internals, multi-modal pipelines.
- Agentic systems: Azure AI Agent Service patterns, MCP servers, registry/broker/governance, secure tool-calling.
- Languages: C# and Python (production-grade), .Net, plus TypeScript for service/UI when needed.
- Azure & AWS services (see Knowledge Requirements) with hands-on implementation and operations.
- Model ops: eval suites, safety tooling, fine-tuning, guardrails, traceability.
- Business & delivery: solution architecture, stakeholder alignment, roadmap planning, measurable impact.
Desired Skills/Abilities (not required but a plus):
- LangChain, Hugging Face, MLflow; Kubernetes + GPU scheduling; vector search tuning (HNSW/IVF).
- Responsible AI: policy mapping, red-team playbooks, incident response for AI.
- Hybrid/multi-cloud deployments using Azure Arc and AWS Outposts; CI/CD for AI workloads across Azure DevOps and AWS CodePipeline.
Step into a high-impact role where AI meets cloud scalability. Apply now and bring cutting-edge solutions to life.